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ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
Contains the IDataView system which is a set of interfaces and components that provide efficient, compositional processing of schematized data for machine learning and advanced analytics applications.
Microsoft.ML.CpuMath contains optimized math routines for ML.NET.
The core of the Accord.NET Framework. Contains basic classes such as general exceptions and extensions used by other framework libraries.
This package contains native shared library artifacts for all supported platforms of ONNX Runtime.
ML.NET component for FastTree
ML.NET component for LightGBM
ML.NET component for Image support
ML.NET additional learners making use of Intel Mkl.
Microsoft.ML.TensorFlow contains ML.NET integration of TensorFlow.
This package contains ONNX Runtime for .Net platforms
ML.NET component for Microsoft.ML.OnnxRuntime.Managed library
Microsoft.ML.Vision contains high level APIs for vision tasks like image classification.
Microsoft.ML.TimeSeries contains ML.NET Time Series prediction algorithms. Uses Intel Mkl.
Google's TensorFlow full binding in .NET Standard.
Building, training and infering deep learning models.
https://tensorflownet.readthedocs.io
Microsoft.ML.Mkl.Redist contains the MKL library redistributed as a NuGet package.
An integration package for ML.NET models on scalable web apps and services.
Official Vowpal Wabbit library including C# interface.
Contains Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.
ML.NET AutoML: Optimizes an ML pipeline for your dataset, by automatically locating the best feature engineering, model, and hyperparameters